RT Journal Article
T1 Molecular diagnosis of polycystic ovary syndrome in obese and non-obese women by targeted plasma miRNA profiling
A1 Romero-Ruiz, Antonio
A1 Pineda, Beatriz
A1 Ovelleiro, David
A1 Perdices-Lopez, Cecilia
A1 Torres, Encarnacion
A1 Vazquez, Maria J.
A1 Guler, Ipek
A1 Jimenez, Alvaro
A1 Pineda, Rafael
A1 Persano, Mariasara
A1 Romero-Baldonado, Cristina
A1 Arjona, Jose E.
A1 Lorente, Juan
A1 Munoz, Concepcion
A1 Paz, Elier
A1 Garcia-Maceira, Fe-Isabel
A1 Arjona-Sanchez, Alvaro
A1 Tena-Sempere, Manuel
K1 Follicular-fluid
K1 Circulating micrornas
K1 Syndrome pcos
K1 Criteria
K1 Identification
K1 Expression
K1 Management
K1 Mechanism
K1 Consensus
K1 Pitfalls
AB Objective: Polycystic ovary syndrome (PCOS) is diagnosed based on the clinical signs, but its presentation is heterogeneous and potentially confounded by concurrent conditions, such as obesity and insulin resistance. miRNA have recently emerged as putative pathophysiological and diagnostic factors in PCOS. However, no reliable miRNAbased method for molecular diagnosis of PCOS has been reported. The aim of this study was to develop a tool for accurate diagnosis of PCOS by targeted miRNA profiling of plasma samples, defined on the basis of unbiased biomarker-finding analyses and biostatistical tools. Methods: A case-control PCOS cohort was cross-sectionally studied, including 170 women classified into four groups: non-PCOS/lean, non-PCOS/obese, PCOS/lean, and PCOS/obese women. High-throughput miRNA analyses were performed in plasma, using NanoString technology and a 800 human miRNA panel, followed by targeted quantitative real-timePCR validation. Statistics were applied to define optimal normalization methods, identify deregulated biomarker miRNAs, and build classification algorithms, considering PCOS and obesity as major categories. Results: The geometric mean of circulating hsa-miR-103a-3p, hsa-miR-125a-5p, and hsa-miR-1976, selected among 125 unchanged miRNAs, was defined as optimal reference for internal normalization (named mR3-method). Ten miRNAs were identified and validated after mR3-normalization as differentially expressed across the groups. Multinomial least absolute shrinkage and selection operator regression and decision-tree models were built to reliably discriminate PCOS vs non-PCOS, either in obese or non-obese women, using subsets of these miRNAs as performers. Conclusions: We define herein a robust method for molecular classification of PCOS based on unbiased identification of miRNA biomarkers and decision-tree protocols. This method allows not only reliable diagnosis of non-obese women with PCOS but also discrimination between PCOS and obesity. Capsule: We define a novel protocol, based on plasma miRNA profiling, for molecular diagnosis of PCOS. This tool not only allows proper discrimination of the condition in non-obese women but also permits distinction between PCOS and obesity, which often display overlapping clinical presentations.
PB Bioscientifica ltd
SN 0804-4643
YR 2021
FD 2021-11-01
LK https://hdl.handle.net/10668/25609
UL https://hdl.handle.net/10668/25609
LA en
DS RISalud
RD Apr 11, 2025